An evo-devo geek's scientific meanderings

Month: November 2013

I take all my hats off to Richard Lenski and his team. If you’ve never heard of them, they are the group that has been running an evolution experiment with E. coli bacteria non-stop for the last 25 years. That’s over 50 000 generations of the little creatures; in human generations, that translates to ~1.5 million years. This experiment has to be one of the most amazing things that ever happened in evolutionary biology.

(Below: photograph of flasks containing the twelve experimental populations on 25 June 2008. The flask labelled A-3 is cloudier than the others: this is a very special population. Photo by Brian Baer and Neerja Hajela, via Wikimedia Commons.)

It doesn’t necessarily take many generations to see some mind-blowing things in evolution. An irreducibly complex new protein interaction (Meyer et al., 2012), the beginnings of new species and a simple form of multicellularity (Boraas et al., 1998) are only a few examples. However, a few generations only show tiny snapshots of the evolutionary process. Letting a population evolve for thousands of generations allows you to directly witness processes that you’d normally have to glean from the fossil record or from studies of their end products.

Fifty thousand generations, for example, can tell you that they aren’t nearly enough time to reach the limit of adaptation. The newest fruit of the Long-Term Evolution Experiment is a short paper examining the improvement in fitness the bacteria experienced over its 25 years (Wiser et al., 2013). “Fitness” is measured here as growth rate relative to the ancestral strain; the faster the bacteria are able to grow in the environment of the LTEE (which has a limited amount of glucose, E. coli‘s favourite food), the fitter they are. The LTEE follows twelve populations, all from the same ancestor, evolving in parallel, so it can also determine whether something that happens to one population is a chance occurrence or a general feature of evolution.

You can draw up a plot of fitness over time for one or more populations, and then fit mathematical models to this plot. Earlier in the experiment, the group found that a simple model in which adaptation slows down over time and eventually grinds to a halt fits the data well. However, that isn’t the only promising model. Another one predicts that adaptation only slows, never stops. Now, the experiment has been running long enough to distinguish between the two, and the second one wins hands down. Thus far, even though they’ve had plenty of time to adapt to their unchanging environment, the Lenski group’s E. coli just keep getting better at living there.

Although the simple mathematical function that describes the behaviour of these populations doesn’t really explain what’s happening behind the scenes, the team was also able to reproduce the same behaviour by building a model from known evolutionary phenomena. For example, they incorporated the idea that two bacteria with two different beneficial mutations in the same bottle are going to compete and slow down overall adaptation. (This is a problem of asexual organisms. If the creatures were, say, animals, they might have sex and spread both mutations at the same time.) So the original model doesn’t just describe the data well, it also follows from sensible theory. So did the observation that the populations which evolved higher mutation rates adapted faster.

Now, one of the first things you learn about interpreting models is that extrapolating beyond your data is dangerous. Trends can’t go on forever. In this case, you’d eventually end up with bacteria that reproduced infinitely fast, which is clearly ridiculous. However, Wiser et al. suggest that the point were their trend gets ridiculous is very, very far in the future. “The 50,000 generations studied here occurred in one scientist’s laboratory in ~21 years,” they remind us, then continue: “Now imagine that the experiment continues for 50,000 generations of scientists, each overseeing 50,000 bacterial generations, for 2.5 billion generations total.”

If the current trend continues unchanged, they estimate that the bugs at that faraway time point will be able to divide roughly every 23 minutes, compared to 55 minutes for the ancestral strain. That is still a totally realistic growth rate for a happy bacterium!

I know none of us will live to see it, but I really want to know what would happen to these little guys in 2.5 billion generations…

Textbooks may portray science as a codification of facts, but it is really a disciplined way of asking about the unknown. — Andrew Knoll, Life on a Young Planet

Some books change your life. When I was 12 or 13 or thereabouts, SJ Gould and others’ Book of Life rekindled my interest in prehistoric life, introduced me to the Cambrian explosion, and opened my eyes to a whole new worldview. It’s one of the reasons I hold a degree in evolutionary biology.

Life on a Young Planet was not a life-changer, precisely. That’s not why I love it to pieces. By the time I read it, I’d gained an appreciation of just how complex and full of uncertainty natural science was, and the book was permeated by an awareness of this complexity. Also, it was simply beautiful writing.

(I can’t emphasise the importance of good writing enough. I’ve read too many papers and books [Crucible of Creation and The Plausibility of Life, I’m looking at you] that had good information but were so atrociously written that I nearly put them down despite being fascinated by their subject.)

Last month, the author of Life on a Young Planet, Harvard professor Andy Knoll, came to visit my university. I was practically bouncing with excitement from the moment I saw his name on a newsletter. He gave four lectures in total; until the very last one, I actually contemplated getting my copy of the book signed. Or, to be a fangirl and a nerd, my printout of his lovely biomineralisation review. (I still can’t decide if I made a mistake. Damn, I didn’t even ask a stupid question. Four lectures, and I just sat there and drooled over my notebook.)

Knoll is nearly as good a speaker as he is a writer. He doesn’t have the liveliest voice and speaks quite slowly, but if you can get past that, his lectures are really good. (I’m glad of that; I really don’t like losing my illusions!) They are solid structures that you have no difficulty following the logic of.

Let me put it this way – Andy Knoll is an excellent storyteller.

That got me worrying, because I’m a sceptic and (truth be told) a little bit of a cynic at heart, and because over the years I’ve done a lot of navel-gazing about belief and knowledge and conviction. I have a tendency to grow suspicious when I feel too certain about something.

Am I – are we – too often blinded by good storytelling? How often do we get so enamoured of good ideas that we try to force them on situations they don’t fit? And how often do we doubt something just because it sounds too neat?

Here’s the specific example from the Knoll lectures that made me think of this. Knoll is a champion of the oxygen + predation explanation of the Cambrian explosion. (I didn’t realise he was involved in that paper until it came up in the lectures…) He is also an advocate of a similar explanation for the diversification of single-celled eukaryotes 250 million years before the Cambrian. He convinced me well enough, but then I immediately thought – really? Is it really that simple? Does one size really fit both events?

I often take note of these “pet ideas” as I read scientific literature. A group of phylogeneticists uses microRNAs to tackle every tough problem ever. A palaeontologist interprets every squishy-looking Cambrian weirdo as a mollusc. Researchers in the biomineral field look for slushy amorphous precursors to crystalline hard parts everywhere. (Remember, all generalisations are false ;))

Just to be clear: I’m not at all saying that being a “pet idea” automatically makes something wrong or suspicious. For instance, the hunters of amorphous biominerals have some good theoretical reasons to look, and they often do find what they’re looking for. Likewise, I’m impressed enough with Andy Knoll’s pet hypothesis about the Cambrian that I’ve rethought my own pet ideas about the subject.

I’m also not accusing these people of being closed-minded. Going back to Knoll, IMO he demonstrated ample healthy scepticism about his pets during his post-lecture Q&A sessions. (Which makes me a bit less nervous about the neatness of his stories.)

Someone better versed in the philosophy and sociology of science could probably write a long treatise involving paradigms and confirmation bias and contrariness here. I’m even less of a philosopher than I am a geologist, so I think I’ll leave the deeper insights to those who have them.

Meanwhile, I’ll continue to be a fan of Andy Knoll and appreciate a good scientific story. So long as I remember to look beneath the surface – both of good stories and of my own suspicion of them…